Top Remote Machine Learning Jobs in Buffalo, NY

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Lead design and delivery of generative AI features end-to-end, prototype and productionize early-stage AI systems, set technical direction, mentor engineers, and collaborate with product and design to drive measurable product impact.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

The ML Engineer will scale automated evaluation systems for AI models, develop judge models, design validation frameworks, and create synthetic data pipelines.

The Group Product Manager will lead the Real Time Decisioning and 3D Secure authentication product suites, focusing on fraud management and security while enhancing customer experiences. Responsibilities include strategy development, cross-functional collaboration, and product optimization.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The VP of Engineering will lead a high-performing team to develop AI-enabled technologies, managing technical vision and execution strategies while ensuring product reliability and security in complex environments.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

As a Lead AI Engineer, design and implement AI and machine learning models and pipelines to enhance healthcare outcomes and efficiency.

The CX Outbound Solution Engineer designs and deploys outbound contact center solutions, focusing on operational efficiency and customer engagement. They work with sales to align solutions with customer needs and lead pilot implementations with a strong grasp of outbound regulations and technologies.

AI Writing Evaluators will create prompts and evaluate AI-generated writing for accuracy and clarity, requiring expertise in business operations or education.

As the Full Stack Support Engineer, you will lead technical support for customers, handle complex technical issues, and collaborate on product feedback and process improvements.

The Director of Software Engineering will lead teams in creating innovative education tech solutions, strategic planning, and optimizing software delivery processes.

The Software Engineering Manager will lead a team in creating tools for Cengage Learning Platforms, focusing on AI innovation, team growth, agile delivery, and collaboration.

The Director of Research Innovation & Enablement will lead AI integration into research, manage researchers, and enhance workflows for insight generation and efficiency.

The Business Development Manager leads strategies for growth in telecom accounts, engaging stakeholders to develop AI/ML-driven solutions, and managing partnerships in a fast-paced environment.

The Sr. Solution Engineer collaborates with Sales to advance enterprise opportunities, conducting demos, workshops, and assessments to align with customer needs and position Aera's Decision Intelligence platform as a transformative solution.

The Senior Technical Recruiter will manage the full-cycle recruiting for technical roles in Data, Machine Learning, and Software Engineering, working closely with engineering leadership to build talent pipelines and evaluate candidates' technical skills.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.